Software Engineer 2

Uber Uber · Consumer · Sunnyvale, CA · Engineering

Software Engineer 2 on the Global Intelligence Team at Uber, focusing on building scalable engineering solutions and platforms for data-driven decision making in Uber Rides and Eats. The role involves implementing and productionizing models, designing new systems for fast data-driven decisions, and building distributed backend systems for real-time analytics and ML features at Uber scale. Collaboration with science and product teams on technical roadmap and vision is key.

What you'd actually do

  1. Work on creating a platform that powers data driven decision making for Uber Rides and Eats line of business
  2. Work very closely with the science team to implement and productionize the models
  3. Design and develop new systems to empower fast data-driven decisions
  4. Build distributed backend systems serving real-time analytics and machine learning features at Uber scale
  5. Work with the product and science teams to build and drive technical roadmap and vision for the team

Skills

Required

  • 2+ years of full-time engineering experience
  • Experience working with multiple multi-functional teams (product, science, product ops etc)
  • Understanding of Big Data architecture, ETL frameworks and platforms
  • Expertise in one or more object-oriented programming languages (e.g. Python, Go, Java, C++)
  • Experience with data-driven architecture and systems design
  • Knowledge of Big Data Technologies
  • BS/MS/Phd in Computer Science or related field

Nice to have

  • Experience building sophisticated systems and knowledge of Hadoop related technologies such as HDFS, Kafka, Hive, and Presto
  • A passion for taking ownership. You pride yourself on efficient monitoring, strong documentation, and accurate test coverage and you call something "done" only when these are in place
  • Building and earning respect within the team and peers. You believe that you can achieve more on a team - that the whole is greater than the sum of its parts. You rely on others' candid feedback for continuous improvement and you help others by returning the favour

What the JD emphasized

  • implement and productionize the models
  • machine learning features

Other signals

  • productionize models
  • real-time analytics and machine learning features
  • data-driven decision making